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A hybrid SUGWO optimization for partial face recognition with new similarity index

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Abstract

This paper introduces a Partial Face Recognition (PFR) method with the benefits of optimization logic using an optimized feature matching aspect. Besides, for better recognition, the Sparse Representation Classification (SRC) and Fully Convolutional Network (FCN) have been combined. As a novelty, this work aims to tune the sparse coefficient of Dynamic Feature Matching (DFM) optimally, in which the reconstruction error should be minimal. Also, this work presents the structural similarity index measure to calculate the similarity scores between the gallery sub-feature map and probe feature map. For optimization purposes, this work deploys a proposed Sealion Updated Grey Wolf Optimization (SUGWO) algorithm. Finally, the proposed method is executed over the traditional methods concerning certain measures.

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Abbreviations

CNNs:

Convolutional Neural Network

DFM:

Dynamic Feature Matching

DL:

Deep Learning

dPFC:

dorsal Prefrontal Cortex

DRUID:

Deep Regression-based User Image Detector

FCNs:

Fully Convolutional Networks

FMRI:

Functional Magnetic Resonance Imaging

FNR:

False Negative Rate

FPR:

False Positive Rate

FR:

Face Recognition

HCI:

Human Computer Interface

HSA:

Harmony Search Algorithm

i-LIDS:

imagery Library for Intelligent Detection Systems

K-NN:

K-nearest Neighbours

LBP:

Local Binary Pattern

LPPLSDA:

Locality Preserving Partial Least Square Discriminant Analysis

MCC:

Mathews Correlation Co-efficient

MFO:

Moth Flame Optimization

MKD-GTP:

Multi-Key point Descriptor with Gabor Ternary Pattern

ML:

Machine Learning

MTLSC:

Model-based Transfer Learning and Sparse Coding

NPV:

Negative Predictive Value

OSPF:

Optimized Symmetric Partial Facegraphs

PCA:

Principal Component Analysis

PFR:

Partial Facial Recognition

PLS-DA:

Partial Least Squares Discriminant Analysis

RE-ID:

Re-identification

RPSM:

Robust Point Set Matching

SGD:

Stochastic Gradient Descent

SIFT:

Scale-Invariant Feature Transform

SRC:

Sparse Representation Classification

SVM:

Support Vector Machine

STS:

Superior Temporal Sulcus

SUGWO:

Sea lion Updated Grey Wolf Optimization

SURF:

Speeded Up Robust Features

TPGM:

Topology Preserving Graph Matching

TPWCRC:

Two-Phase Weighted collaborative Representation Classification

WOA:

Whale Optimization Algorithm

3D:

Three Dimension

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, 324010, India

    Ganesh Gopalrao Patil & Rohitash Kumar Banyal

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  1. Ganesh Gopalrao Patil
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Correspondence to Ganesh Gopalrao Patil.

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Patil, G.G., Banyal, R.K. A hybrid SUGWO optimization for partial face recognition with new similarity index. Multimed Tools Appl 82, 18097–18116 (2023). https://doi.org/10.1007/s11042-022-14205-z

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